Today there is a plethora of computer software programs which allow for the collection, organization and analysis of data from many different sources and fields of study. Financial institutions in particular rely heavily on computer systems and programs to run the myriad of investment options and strategies for their clients and depositors. The current school of thought encourages the investment of one savings into financial opportunities other than the traditional savings account. The stock market in general has out-performed and provided greater rates of return for money invested than savings accounts over the last 15-20 years.
Investment in these types of securities however always carries risk be it through the direct purchase of a company's stock listed on one of the many markets or through the purchase of mutual funds and/or money market shares. Prudent investment in these areas requires the ability to analyze carefully how a company or financial market has performed in the past and its expectations for the future. In this manner one can hope to forecast what a financial security such as a company's stock or a financial securities market will do in order to purchase financial securities or focus on financial securities markets that will go up in value and provide the greatest rate of return.
Unfortunately, even after careful analysis the ability to project the future activity and performance of a financial security or financial market is never a sure thing and the investor can only hope these expectations will come to fruition. Nevertheless, many financial planners and creators of investment portfolios try to project the future performance of financial securities and financial security markets with varying results. It would be highly advantageous then, if one could monitor a financial market or financial security and analyze the vast amount of data collected therefrom using indicators that would be helpful to an analyst or that analysts employ in trying to project the future performance of that market or security.
Computer systems for monitoring and analyzing data from physiological and physical sources are known in the art. Seismographs for example, are well known sensors for the detection of tremors below the earth's crust and this data can be used to predict when and where an earthquake will occur.
U.S. Pat. No. 4,796,639 to Snow et al. discloses and claims a pulmonary diagnostic system in which a computer records and stores lung physiology data and compares recorded values with expected norms. Based on the comparison, the computer generates certain values (if so recorded) as abnormal and the degree of abnormality as a function of a baseline. This can then be used to immediately sense and/or predict pulmonary problems or early signs thereof for preventive treatment.
U.S. Pat. No. 4,834,107 to Warner discloses and claims a non-invasive method for determining heart-related parameters in patients. The apparatus measures a number of physiological changes such as pulse pressure, peripheral resistance, systolic and diastolic pressure, cardiac output and the like. These are then fed into a number of mathematical formulae which when computed as a function is indicative of the state of the system and when that system falls outside the healthy norm. This can then be used to predict the likelihood of future problems in the patient.
U.S. Pat. No. 5,355,889 to Nevo et al. discloses a patient monitoring system which collects and analyzes a plurality of different medical parameters derived from a human subject. Particularly useful in the monitoring of the bodily functions of a patient under anesthesia during surgery, the system monitors the physiological parameters and transforms them into a sigmoid function indicative of normal and critical levels of that physiological parameter. A comparison of maximum and minimum function values with a baseline value produces a vital function status indicator which not only provides a reasonable assessment of the patient's condition, but also what parameter(s), if any, are responsible for a patient's deteriorating condition.
U.S. Pat. No. 5,465,308 to Hutcheson et al. discloses and claims a pattern recognition system comprised of a software program and method for its use which utilizes a neural network implementation to recognize the similarity of information received compared to that stored in a database. Two dimensional images are subjected to Fourier Transformation to yield a power spectrum. From this spectrum, output vectors are generated which are statistically analyzed to determine any correlations between known patterns of data stored and that coming in. Whereas the main function is the matching of facial patterns, other applications are allegedly possible.
The above-described systems provide a basic means for the monitoring of multiple parameters either for the diagnosis of and solution to a problem or for the evaluation of the condition of an entity which, through analysis, reasonably would give one a well founded basis to anticipate possible future changes. Many other such systems in control applications exist in the art but none provide the ability to monitor a number of parameters which can be transformed into a single indicator for use in projecting performance of specific financial securities or financial securities markets.
U.S. patent application Ser. No. 08/647,396, which is a companion application to the present application by the same inventor, discloses an apparatus and method for monitoring a system, such as a patient, to provide information regarding the status of the system. The use of a system criticality indicator to convey information about the overall status of the system is described. The system criticality indicator (DI.sub.cri) is defined as: ##EQU1## wherein n is the total number of parameters being measured, DI.sub.max is the maximum deviation indicator for all of the measured parameters, n.sub.m is the total number of parameters with a deviation indicator equal to the maximum deviation indicator, and DI.sub.avg is the average of the deviation indicators for each measured parameter.
In light of the above, it would be advantageous to provide an apparatus and method for monitoring a security or financial market wherein an overwhelmingly large amount of data is consolidated to provide the user with a manageable amount of information from which he could better assess the condition of a security or financial market. Preferably, the apparatus and method is responsive to the particularities of the user and the specific security or financial market being monitored. In addition, the apparatus and method should be rapid enough to provide information in real-time or at any specified time.